Estimates
Bias
load("./datasets/simAllen50_bias.rda")
K <- 1:4
ggplot(bias[bias$param == 'beta_mu', ], aes(x = K, y = bias)) +
geom_boxplot() + ggtitle('beta_mu') + facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red')

ggplot(bias[bias$param == 'beta_pi', ], aes(x = K, y = bias)) +
geom_boxplot() + ggtitle('beta_pi') + facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red')

ggplot(bias[bias$param == 'beta_pi', ], aes(x = K, y = bias)) +
geom_boxplot(outlier.shape = NA) + ggtitle('beta_pi, no outlier') +
facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red') +
coord_cartesian(ylim = c(-30,15))

ggplot(bias[bias$param == 'beta_pi', ], aes(x = V, y = bias)) +
geom_boxplot() + ggtitle('beta_pi') + facet_grid(disp ~ K) +
geom_hline(yintercept = 0, col = 'red')

ggplot(bias[bias$param == 'gamma_mu', ], aes(x = K, y = bias)) +
geom_boxplot() + ggtitle('gamma_mu') + facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red')

ggplot(bias[bias$param == 'gamma_mu' & bias$V == 'V', ],
aes(x = K, y = bias)) +
geom_boxplot() + ggtitle('gamma_mu') + facet_grid( ~ disp) +
geom_hline(yintercept = 0, col = 'red')

ggplot(bias[bias$param == 'gamma_pi', ], aes(x = K, y = bias)) +
geom_boxplot() + ggtitle('gamma_pi') + facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red')

ggplot(bias[bias$param == 'gamma_pi' & bias$V == 'V', ],
aes(x = K, y = bias)) +
geom_boxplot() + ggtitle('gamma_pi') + facet_grid( ~ disp) +
geom_hline(yintercept = 0, col = 'red')

ggplot(bias[bias$param == 'gamma_pi' & bias$V == 'V', ],
aes(x = K, y = bias)) +
geom_boxplot(outlier.shape = NA) + ggtitle('gamma_pi, no outlier') +
facet_grid( ~ disp) + coord_cartesian(ylim = c(-.5,.5)) +
geom_hline(yintercept = 0, col = 'red')

ggplot(bias[bias$param == 'theta', ], aes(x = K, y = bias)) +
geom_boxplot() + ggtitle('theta') + facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red')

ggplot(bias[bias$param == 'theta', ],
aes(x = disp, y = bias)) +
geom_boxplot() + ggtitle('theta') + facet_grid(V ~ K) +
geom_hline(yintercept = 0, col = 'red')

ggplot(bias[bias$param == 'walpha_mu', ], aes(x = K, y = bias)) +
geom_boxplot() + ggtitle('walpha_mu') + facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red')

ggplot(bias[bias$param == 'walpha_mu', ],
aes(x = interaction(disp, K, V), y = bias)) +
geom_boxplot() + ggtitle('walpha_mu') + xlab('') +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
geom_hline(yintercept = 0, col = 'red')

ggplot(bias[bias$param == 'walpha_mu', ],
aes(x = interaction(disp, K, V), y = bias)) +
geom_boxplot(outlier.shape = NA) + xlab('') +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
geom_hline(yintercept = 0, col = 'red') +
coord_cartesian(ylim = c(-2,2)) + ggtitle('walpha_mu, no outlier')

ggplot(bias[bias$param == 'walpha_pi', ], aes(x = K, y = bias)) +
geom_boxplot() + ggtitle('walpha_pi') + facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red')

ggplot(bias[bias$param == 'walpha_pi', ],
aes(x = interaction(disp, K, V), y = bias)) +
geom_boxplot() + ggtitle('walpha_pi') + xlab('') +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
geom_hline(yintercept = 0, col = 'red')

ggplot(bias[bias$param == 'walpha_pi', ],
aes(x = interaction(disp, K, V), y = bias)) +
geom_boxplot(outlier.shape = NA) + xlab('') +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
geom_hline(yintercept = 0, col = 'red') +
coord_cartesian(ylim = c(-10,10)) + ggtitle('walpha_pi, no outlier')

ggplot(bias[bias$param == 'mu', ], aes(x = K, y = bias)) +
geom_boxplot() + ggtitle('mu') + facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red')

ggplot(bias[bias$param == 'mu', ], aes(x = K, y = bias)) +
geom_boxplot(outlier.shape = NA) + ggtitle('mu, no outlier') +
facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red') + coord_cartesian(ylim = c(-2,2))

ggplot(bias[bias$param == 'pi', ], aes(x = K, y = bias)) +
geom_boxplot() + ggtitle('pi') + facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red')

ggplot(bias[bias$param == 'pi', ], aes(x = K, y = bias)) +
geom_boxplot(outlier.shape = NA) + ggtitle('pi, no outlier') +
facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red') + coord_cartesian(ylim = c(-25,25))

Variance
load("./datasets/simAllen50_variance.rda")
K <- 1:4
ggplot(variance[variance$param == 'beta_mu', ], aes(x = K, y = variance)) +
geom_boxplot() + ggtitle('beta_mu') + facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red')

ggplot(variance[variance$param == 'beta_pi', ], aes(x = K, y = variance)) +
geom_boxplot() + ggtitle('beta_pi') + facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red')

ggplot(variance[variance$param == 'gamma_mu', ], aes(x = K, y = variance)) +
geom_boxplot() + ggtitle('gamma_mu') + facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red')

ggplot(variance[variance$param == 'gamma_mu' & variance$V == 'V', ],
aes(x = K, y = variance)) +
geom_boxplot() + ggtitle('gamma_mu') + facet_grid( ~ disp) +
geom_hline(yintercept = 0, col = 'red')

ggplot(variance[variance$param == 'gamma_pi', ], aes(x = K, y = variance)) +
geom_boxplot() + ggtitle('gamma_pi') + facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red')

ggplot(variance[variance$param == 'gamma_pi' & variance$V == 'V', ],
aes(x = K, y = variance)) +
geom_boxplot() + ggtitle('gamma_pi') + facet_grid( ~ disp) +
geom_hline(yintercept = 0, col = 'red')

ggplot(variance[variance$param == 'theta', ], aes(x = K, y = variance)) +
geom_boxplot() + ggtitle('theta') + facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red')

ggplot(variance[variance$param == 'theta', ],
aes(x = disp, y = variance)) +
geom_boxplot() + ggtitle('theta') + facet_grid(V ~ K) +
geom_hline(yintercept = 0, col = 'red')

ggplot(variance[variance$param == 'walpha_mu', ], aes(x = K, y = variance)) +
geom_boxplot() + ggtitle('walpha_mu') + facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red')

ggplot(variance[variance$param == 'walpha_mu', ],
aes(x = interaction(disp, K, V), y = variance)) +
geom_boxplot() + ggtitle('walpha_mu') + xlab('') +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
geom_hline(yintercept = 0, col = 'red')

ggplot(variance[variance$param == 'walpha_pi', ], aes(x = K, y = variance)) +
geom_boxplot() + ggtitle('walpha_pi') + facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red')

ggplot(variance[variance$param == 'walpha_pi', ],
aes(x = interaction(disp, K, V), y = variance)) +
geom_boxplot() + ggtitle('walpha_pi') + xlab('') +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
geom_hline(yintercept = 0, col = 'red')

ggplot(variance[variance$param == 'mu', ], aes(x = K, y = variance)) +
geom_boxplot() + ggtitle('mu') + facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red')

ggplot(variance[variance$param == 'pi', ], aes(x = K, y = variance)) +
geom_boxplot() + ggtitle('pi') + facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red')

MSE
mse = bias
colnames(mse)[1] = c('mse')
mse$mse = bias$bias^2 + variance$variance
ggplot(mse[mse$param == 'beta_mu', ], aes(x = K, y = mse)) +
geom_boxplot() + ggtitle('beta_mu') + facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red')

ggplot(mse[mse$param == 'beta_mu', ], aes(x = K, y = mse)) +
geom_boxplot(outlier.shape = NA) + ggtitle('beta_mu, no outlier') +
facet_grid(disp ~ V) + coord_cartesian(ylim = c(0,75)) +
geom_hline(yintercept = 0, col = 'red')

ggplot(mse[mse$param == 'beta_mu' & mse$V == 'V', ], aes(x = K, y = mse)) +
geom_boxplot(outlier.shape = NA) + ggtitle('beta_mu, no outlier') +
facet_grid(disp ~ V) + coord_cartesian(ylim = c(0, .2)) +
geom_hline(yintercept = 0, col = 'red')

ggplot(mse[mse$param == 'beta_pi', ], aes(x = K, y = mse)) +
geom_boxplot() + ggtitle('beta_pi') + facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red')

ggplot(mse[mse$param == 'beta_pi', ], aes(x = K, y = mse)) +
geom_boxplot(outlier.shape = NA) + ggtitle('beta_pi, no outlier') +
facet_grid(disp ~ V) + coord_cartesian(ylim = c(0,1600)) +
geom_hline(yintercept = 0, col = 'red')

ggplot(mse[mse$param == 'gamma_mu' & mse$V == 'V', ],
aes(x = K, y = mse)) +
geom_boxplot() + ggtitle('gamma_mu') + facet_grid( ~ disp) +
geom_hline(yintercept = 0, col = 'red')

ggplot(mse[mse$param == 'gamma_pi' & mse$V == 'V', ],
aes(x = K, y = mse)) +
geom_boxplot() + ggtitle('gamma_pi') + facet_grid( ~ disp) +
geom_hline(yintercept = 0, col = 'red')

ggplot(mse[mse$param == 'gamma_pi' & mse$V == 'V', ],
aes(x = K, y = mse)) +
geom_boxplot(outlier.shape = NA) + ggtitle('gamma_pi, no outlier') +
facet_grid( ~ disp) + coord_cartesian(ylim = c(0,.2)) +
geom_hline(yintercept = 0, col = 'red')

ggplot(mse[mse$param == 'theta', ], aes(x = K, y = mse)) +
geom_boxplot() + ggtitle('theta') + facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red')

ggplot(mse[mse$param == 'theta', ], aes(x = K, y = mse)) +
geom_boxplot(outlier.shape = NA) + ggtitle('theta, no outlier') +
facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red') + coord_cartesian(ylim = c(0,1.5))

ggplot(mse[mse$param == 'walpha_mu', ], aes(x = K, y = mse)) +
geom_boxplot() + ggtitle('walpha_mu') + facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red')

ggplot(mse[mse$param == 'walpha_mu', ],
aes(x = interaction(disp, K, V), y = mse)) +
geom_boxplot() + ggtitle('walpha_mu') + xlab('') +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
geom_hline(yintercept = 0, col = 'red')

ggplot(mse[mse$param == 'walpha_mu', ],
aes(x = interaction(disp, K, V), y = mse)) +
geom_boxplot(outlier.shape = NA) + ggtitle('walpha_mu, no outlier') +
xlab('') + coord_cartesian(ylim = c(0,2)) +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
geom_hline(yintercept = 0, col = 'red')

ggplot(mse[mse$param == 'walpha_pi', ], aes(x = K, y = mse)) +
geom_boxplot() + ggtitle('walpha_pi') + facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red')

ggplot(mse[mse$param == 'walpha_pi', ],
aes(x = interaction(disp, K, V), y = mse)) +
geom_boxplot() + ggtitle('walpha_pi') + xlab('') +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
geom_hline(yintercept = 0, col = 'red')

ggplot(mse[mse$param == 'walpha_pi', ],
aes(x = interaction(disp, K, V), y = mse)) +
geom_boxplot(outlier.shape = NA) + ggtitle('walpha_pi, no outlier') +
xlab('') + coord_cartesian(ylim = c(0,1000)) +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
geom_hline(yintercept = 0, col = 'red')

ggplot(mse[mse$param == 'mu', ], aes(x = K, y = mse)) +
geom_boxplot() + ggtitle('mu') + facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red')

ggplot(mse[mse$param == 'mu', ], aes(x = K, y = mse)) +
geom_boxplot(outlier.shape = NA) + ggtitle('mu, no outlier') +
facet_grid(disp ~ V) + coord_cartesian(ylim = c(0,2)) +
geom_hline(yintercept = 0, col = 'red')

ggplot(mse[mse$param == 'pi', ], aes(x = K, y = mse)) +
geom_boxplot() + ggtitle('pi') + facet_grid(disp ~ V) +
geom_hline(yintercept = 0, col = 'red')

ggplot(mse[mse$param == 'pi', ], aes(x = K, y = mse)) +
geom_boxplot(outlier.shape = NA) + ggtitle('pi, no outlier') +
facet_grid(disp ~ V) + coord_cartesian(ylim = c(0,2000)) +
geom_hline(yintercept = 0, col = 'red')
